Machine Learning - Lead ML Engineering

The Role

We're looking for a senior AI engineer who can build production-grade agentic AI systems. You'll be working at the intersection of cutting-edge AI research and scalable engineering, creating autonomous agents that can reason, plan, and execute complex tasks reliably at scale.

What We Need

Agentic AI & LLM Engineering

You should have hands-on experience with:

Multi-agent systems

Agent orchestration

LLMOps Experience

AI Observability

Evaluation frameworks

LLM inference optimization

Systems Engineering

Strong backend development skills including:

Python expertise

Distributed systems

Database strategy

Web-scale design

DevOps (Non-negotiable)

Kubernetes

Containerization

CI/CD

Infrastructure as Code

Monitoring

Programing Language : Java , Python

What You'll Build

You'll architect the infrastructure that powers our autonomous AI systems:

Agent Orchestration Platform

Evaluation Infrastructure

Production AI Services

Training Systems

Who You Are

You've spent serious time in production environments building AI systems that actually work. You understand the unique challenges of agentic AI - managing state across long conversations, handling partial failures in multi-step processes, and ensuring agents stay aligned with their intended goals.

You've dealt with the reality that the hardest problems aren't always algorithmic. Sometimes it's about making an agent retry gracefully when an API call fails, or designing an observability layer that catches when an agent starts behaving unexpectedly, or building systems that can scale from handling dozens of agent interactions to millions.

You're excited about the potential of AI agents but pragmatic about the engineering work required to make them reliable in production.